Characteristics of resting-state electroencephalogram microstates in individuals with different levels of depressive symptoms

Objective To explore the characteristics of electroencephalogram (EEG) microstates of individuals with different levels of depressive symptoms in resting state so as to provide objective biomarkers in screening and identification of depressive symptoms in the population. Methods A total of 129 healthy volunteers aged 18 to 40 years were recruited from July to October 2020 in Chongqing. According to the results of Self-Rating Depression Scale (SDS), they were divided into following 3 groups: non-depressive group (n=107), mild depressive group (n=18) and moderate to severe depressive group (n=4). EEG signals of subjects in 8-min resting state were collected, and then were preprocessed and analyzed by MATLAB, EEGLAB and other tools to obtain 4 types (A, B, C and D) of microstate and their parameters, including global explanation variance (GEV), duration, occurrence frequency, coverage rate and conversion rate. SPSS24.0 was used for statistical analysis of each parameter. Results ① Among the subjects, 17.05% showed depressive symptoms. The average GEV of resting EEG microstates in healthy volunteers was 76.49%. ②The mean duration of microstate A in the mild depressive group was lower than that in the non-depressive and moderate to severe depressive group (P < 0.001). ③EEG microstate A had higher occurrence frequency than the other 3 types of microstates in the non-depressive and moderatet to severe depressive group (P < 0.001). ④The mild depressive group presented lower coverage rate of microstate A than the other 2 groups (P < 0.001). ⑤There were differences in conversion rates among different types of microstates (P < 0.05). Conclusion The duration of microstate A may be an early warning signal of the occurrence and development of depressive symptoms, which characterizes the preclinical state of depression. The declined conversion rate of microstates A and C may indicate the occurrence of depressive symptoms, and the alteration in the conversion rate of microstates C and D may be a key feature of the development and progression of depressive symptoms.